WO2021246642A1 - Procédé de recommandation de police de caractères et dispositif destiné à le mettre en œuvre - Google Patents

Procédé de recommandation de police de caractères et dispositif destiné à le mettre en œuvre Download PDF

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Publication number
WO2021246642A1
WO2021246642A1 PCT/KR2021/005071 KR2021005071W WO2021246642A1 WO 2021246642 A1 WO2021246642 A1 WO 2021246642A1 KR 2021005071 W KR2021005071 W KR 2021005071W WO 2021246642 A1 WO2021246642 A1 WO 2021246642A1
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WIPO (PCT)
Prior art keywords
font
list
characteristic information
user
fonts
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PCT/KR2021/005071
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English (en)
Korean (ko)
Inventor
정현제
김재욱
김원준
박용락
윤정환
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(주)폰트릭스
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Publication of WO2021246642A1 publication Critical patent/WO2021246642A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/103—Formatting, i.e. changing of presentation of documents
    • G06F40/109—Font handling; Temporal or kinetic typography
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/12—Use of codes for handling textual entities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/211—Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars

Definitions

  • the present invention relates to a method for recommending a font and an apparatus for implementing the same, and more particularly, to a method for securing text based on a font, a document, and a font, and an apparatus for implementing the same.
  • fonts can be applied to variously written text documents to preserve the individuality of the documents.
  • it is difficult for users to easily determine which font to use.
  • the present invention is to provide AI (Artificial Intelligence) recommended font technology to classify and integrate various fonts by adding various meta information or tags to the font to recommend a font that best corresponds to the information input by the user.
  • AI Artificial Intelligence
  • the present invention makes it possible to recommend more various fonts through the connection between meta information about fonts and images, fonts and colors, fonts and objects.
  • the present invention makes it possible to recommend a font by providing tags or characteristic information as a relational network characteristic for a font and each meta information (tag) group.
  • a method of recommending a font includes the steps of: selecting, by a control unit of a server, a candidate for group-specific characteristic information applicable to a first font by using a first font or meta information about the first font; Registering, by the controller, first characteristic information among candidates selected by reflecting group-specific characteristic information of a second font that is distinguished from the first font and whose characteristic information is registered before the first font, in the first font;
  • the control unit compares the group-specific characteristic information with the context or context characteristic information to generate a recommended font list comprising at least one of the first font and the second font.
  • the server for recommending a font selects a candidate for group-specific characteristic information applicable to the first font using the first font or meta information about the first font, and is distinguished from the first font.
  • various fonts can be recommended through a connection between meta information about a font and an image, a font and a color, and a font and an object.
  • a font can be recommended by providing tags or characteristic information based on the relational characteristics of the font and each meta information (tag) group.
  • FIG. 1 is a diagram showing an interaction between a server and a client according to an embodiment of the present invention.
  • FIG. 2 is a diagram showing the configuration of a server according to an embodiment of the present invention.
  • FIG. 3 is a view showing an operation process of a font list collection and a characteristic register according to an embodiment of the present invention.
  • FIG. 4 is an example of a relationship diagram generated by a font list collection and a characteristic register according to an embodiment of the present invention.
  • FIG. 5 is a diagram illustrating a process of recommending a font by an intelligent font characteristic analyzer according to an embodiment of the present invention.
  • FIG. 6 is a diagram illustrating a process of extracting a font list in response to context characteristic information according to an embodiment of the present invention.
  • FIG. 7 is a view showing a similarity measurement process of fonts according to an embodiment of the present invention.
  • FIG. 8 is a diagram showing the operation process of the font use list intelligent analyzer according to an embodiment of the present invention.
  • FIG. 9 is a diagram illustrating a process of recommending a font based on a font use list according to an embodiment of the present invention.
  • FIG. 10 is a diagram illustrating a process of analyzing a big data-based font trend and recommending a font according to an embodiment of the present invention.
  • FIG. 11 is a diagram illustrating an operation process of a font intelligent curation service provider according to an embodiment of the present invention.
  • FIG. 12 is a diagram in which the server according to an embodiment of the present invention graphs the degree of association of characteristic information for each font.
  • FIG. 13 is a diagram in which a server arranges fonts in a two-dimensional space using characteristic values of two pieces of characteristic information for each font according to an embodiment of the present invention.
  • FIG. 14 is a diagram in which the server according to an embodiment of the present invention arranges users in a two-dimensional space using the preference of two font lists for each user.
  • the server 300 receives document information provided by each of the clients 100, 100a, 100b, ..., 100n or identification information or search information of each of the clients 100a, 100b, ..., 100n.
  • the server 300 receives font information selected by each of the clients 100a, 100b, ..., 100n.
  • Clients 100a, 100b, ..., 100n refer to client devices, and all devices capable of creating documents using fonts, such as notebooks, computers, mobile phones, and tablets, are an embodiment.
  • the server 300 may internally store information on a font that can be recommended in response to a specific situation or transmit it to the individual clients 100a, 100b, ..., 100n.
  • the server 300 recommends a font based on each client's font usage history or document writing situation, document name, document writing situation, such as words appearing in the document, or clients' past font use history, etc., and font information applied by clients can be accumulated to create new font recommendation information.
  • Embodiments in the present specification suggest a method of recommending a font by reflecting multidimensional font characteristic information of a font, a user's preferred font, and a trend for the font.
  • the multidimensional font characteristic information of a font means that fonts and characteristic information are connected according to various groups or criteria.
  • the server 300 and the client 100 show a separated embodiment.
  • the client 100 includes the configuration of the server 300 , and the client 100 may provide a service provided by the server 300 . This means that data provided by the server 300 is stored in the client 100 and the client 100 processes the data.
  • the client 100 may directly recommend a font or font lists based on certain data received from the outside.
  • the communication unit 310 is a component that communicates with clients.
  • the controller 350 collects information necessary for recommending a font, and recommends a font using the collected information.
  • the storage unit 320 stores a list related to the font recommendation generated by the control unit 350, that is, lists.
  • the control unit 350 updates the lists stored in the storage unit 320 based on the use situation of fonts or changes in trends.
  • the control unit 350 includes a font list collection and characteristic register 351 , a font characteristic intelligent analyzer 353 , a font use list intelligent analyzer 354 , a font trend intelligent analyzer 355 , and a font intelligent curation service provider 358 .
  • the control unit 350 may provide all the functions of the above-described components and constitute one piece of hardware or one piece of software.
  • the control unit 350 itself may be a part of one piece of hardware or a piece of software constituting the server 300 .
  • descriptions of respective components also correspond to descriptions of functions provided by the control unit 350 .
  • the font list collection and characteristic register 351 may collect information on which a client applies a font to a specific document or specific text, information related to the client's use of the font, and the like.
  • the collected information is input to the font characteristic intelligent analyzer 353, the font usage list intelligent analyzer 354, and the font trend intelligent analyzer 355, respectively, and these analyzers generate font recommendation information, respectively.
  • the font recommendation information includes information (eg, a name of a font) about a font that can be recommended in response to a specific document/text, or characteristics of a font input by a user.
  • the font intelligent curation service provider 358 may generate a list of fonts of various categories using the font recommendation information generated by the three analyzers 353 , 354 , and 355 . Also, the intelligent font curation service provider 358 may generate a new font list using both the font list and font recommendation information stored in the storage unit 320 .
  • the configuration of the server of FIG. 2 is summarized as follows.
  • the control unit 350 selects a candidate for group-specific characteristic information applicable to the first font by using the first font or meta information about the first font, is distinguished from the first font, and registers characteristic information before the first font The first characteristic information among the candidates selected by reflecting the group-specific characteristic information of the selected second font is registered in the first font.
  • the communication unit 310 may receive context or context characteristic information from the client 100 .
  • identification information of a user logged into the client 100 may be received, or trend collection information may be received from the outside.
  • control unit 350 may generate a recommended font list including any one or more of the first font and the second font by comparing the group-specific characteristic information and the context or context characteristic information.
  • the context refers to a document or file to which a font is applied as an embodiment.
  • the context refers to images and videos in various formats included in a web page to which a font is applied as an embodiment.
  • the context characteristic information refers to characteristic information inferred from a context as an embodiment.
  • the recommended font method does not stop at a simple search function of a font.
  • the server 300 of FIG. 2 may reflect a multidimensional font classification, the needs and tendencies of a client (or a user possessing the client), and the type of document to be prepared. In this process, one or more recommended fonts can be used to reflect the user's request for font use.
  • the AI recommendation font service provided by the server 300 of FIG. 2 includes a characteristic-based recommendation method that recommends a font based on multi-dimensional characteristic information set in the font, a history recommendation method based on the user's font list, and a big data-based font trend It is possible to recommend fonts by mixing trend-based recommendation methods.
  • the server 300 may provide an artificial intelligent font recommendation service (or AI recommended font service).
  • the AI recommendation font service provides an intelligent font curation service, which solves the difficulties that users have in choosing a font, and goes beyond the existing standardized font classification method, and is suitable for a variety of uses, styles, and emotions. can help you choose them.
  • the server 300 may classify the characteristics of fonts by applying artificial intelligence to various users' font usage patterns, characteristic information previously input to each font, or tag information input by a user. And, the server 300 may generate font recommendation information based on the classified characteristics. For this, the server 300 may configure a font classification system differently. The operation of the font list collection and the characteristic register 351 for performing classification and registering the characteristics of the font by using the characteristics of the font will be described in more detail.
  • FIG. 3 is a view showing an operation process of a font list collection and a characteristic register according to an embodiment of the present invention.
  • the font list collection and characteristic register 351 may receive a font input from the communication unit 310 .
  • the registrar may automatically collect the font list.
  • the register 351 registers characteristics for each typeface name, characteristics for each style, characteristics for each emotion, characteristics for each use, characteristics for each user (client), and characteristics for each image/object in correspondence with the font.
  • the register 351 registers the above-described characteristics in response to the name of the font or identification information for identifying the font.
  • the register 351 may generate a relationship diagram according to the registered characteristics.
  • the register 351 may be a font name, style, sensibility, use, user, image/object, etc., which are exemplary and other groups may also be added.
  • Groups that can have the characteristics of each font can be divided into large typeface classification group, style group, emotion group, use group, image/object group, custom group, etc., and new groups can be added at any time and new characteristics to each group can be added.
  • characteristic information registered in correspondence to fonts for each group are as follows.
  • "#" may be displayed in front of the characteristic information, but this is exemplary and other special characters may be combined.
  • the characteristic information may be composed of words without a separate special character. That is, when the server 300 processes and stores the characteristic information, a special character such as “#” may be excluded.
  • the first group includes characteristic information such as #text, #trendy, #handwriting, and #fancy belonging to the font type. You can use the font name.
  • the second group includes #Gothic, #Myeongjo, #Rollim, #Help, #Square, #Talquare, #Readability, #Serif, #Thick, #Long, #Round, etc. characteristic information of
  • the tertiary group, the “emotional” group includes #modern, #modern, #digital, #sensual, #fluttering, #cool, #welcome, #laugh, #joy, #surprising, #fresh, #cheerful, #bright, # Character information such as cute, #glamorous, #slow, etc. may be included, and there is no limit to adding new characteristics.
  • the 4th group "Use” group, includes characteristic information such as #report, #mail, #text, #business, #blog, #diary, #subtitle.
  • the 5th group “Image/Things”, includes #corporate, #public office, #coffee, #gift, #baby, #dog, #scent, #stamp, #sticker, #desert, #blue, #memory, #heart, #Star, #Angel, #Cloud, #Princess, #Music, #Decoration, #Firework, #Pink, #Pig, #Heart, #Freedom, #Moon, etc. Names, colors, abstraction/symbol expressions, smells, etc. Characteristic information such as images and objects that the font fits well are included.
  • the "user-defined" group various characteristic information that the user adds as needed can be specified.
  • examples of the characteristic information entered by the user using a specific font include #report, #proposal, #photo, #anniversary, #candy, #sweet, #homepage, etc.
  • the register 351 may determine when adding characteristics so as not to add previously defined characteristics as duplicates.
  • the characteristics of the 5th group, "image/object” group can be more powerful when used in conjunction with an AI-based object recognition program. For example, when a dog or dog picture included in a document or web page to which the font is to be applied is recognized using the AI camera's AI object recognition program, the string "dog" is presented.
  • the register 351 may register characteristic information corresponding to each font in the aforementioned groups. Such registration may be performed manually by an administrator, or the register 351 may automatically extract from the description data for the font. Alternatively, the server 300 may analyze the characteristic information added by the user in the course of using the fonts, or the used documents, images, websites, etc., which are fonts, and register the characteristic information. The registration process includes updating or adding/deleting existing registered characteristic information.
  • the font list collection and characteristic register 351 registers the characteristic information of the font for each font
  • the font is defined based on various characteristic information.
  • the server 300 may more easily search for a font desired by the user by reflecting the registered characteristic information and provide it. Compared to searching only by font name and style classification, it is possible to search for fonts suitable for documents, images, texts, etc. to be used for fonts based on a diverse and new classification system.
  • the register 351 registers the font name characteristic information of #Rix Gothic from the font name in the name of the font or in the explanatory material for the font. can register.
  • the register 351 may load various characteristic information and register it as characteristic information of the corresponding font, "Rix Gothic".
  • style characteristic information such as #Gothic and #Basic can be registered in the name of the corresponding font or in the description material for the corresponding font.
  • the register 351 may register #modern and #strict as emotional characteristic information in the name of the corresponding font or in the description data for the corresponding font.
  • the register 351 may register the name of the corresponding font or the use characteristic information of the #report, #text, #mail, #official, #thesis, #business, #resume, etc.
  • the register 351 may use the emotional characteristic information. That is, the register 351 may extract #report, #text, #thesis, #business, etc., which are usage characteristic information linked to emotional characteristic information of #modern and #strict.
  • the register 351 in the process of registering the characteristics of a font called "Rix language", which is a new font, the name of the font or the typeface name of #Rix language from the typeface name in the explanatory material for the corresponding font Characteristic information can be registered.
  • the register 351 in response to the name of the font "Rix language” being onomatopoeic, the register 351 may load various characteristic information and register it as characteristic information of the corresponding font "Rix French”.
  • the register 351 may register the style characteristic information of #handwriting in the name of the corresponding font or description data for the corresponding font.
  • the register 351 may register the style characteristic information by using the font name including the onomatopoeia of "hehe language" as described above.
  • the register 351 may register #modern, #slow, #alone, etc. as emotional characteristic information in the name of the corresponding font or description data for the corresponding font.
  • the register 351 may register a #diary, #diary, #blog, etc., which are usage characteristic information in the name of the corresponding font or description data for the corresponding font.
  • the register 351 may use the emotional characteristic information. That is, the register 351 may extract #diary, #diary, #blog, etc., which are usage characteristic information linked to emotional characteristic information of #modern, #slow, and #alone.
  • #character, #emotion, #sigh, #slowness, etc. can be registered as user characteristic information
  • #individual etc. can be registered as image/object characteristic information. From the characteristics of the word "heo" in the above-mentioned font name, the register 351 may apply artificial intelligence to automatically generate characteristic information.
  • the register 351 may generate a relationship diagram in which each font and their correspondence are reflected based on the above-described embodiments.
  • the registration process described with reference to FIG. 3 may be directly performed by the controller 350 .
  • the register 351 is a sub-component of the control unit 350 and may be integrally included in the control unit 350 .
  • the control unit 350 may select a candidate for the characteristic information for each group applicable to the first font by using the first font or meta information about the first font.
  • the meta information about the first font includes description information and name information about the first font.
  • the controller 350 may select a candidate for group-specific characteristic information applicable to the first font by using them. Using the font name “Rix Gothic” and meta information “for report”, the controller 350 controls “Gothic” as style characteristic information, “Modern” as emotional characteristic information, “report” as usage characteristic, and user-defined characteristic You can select "Report” or "Proposal”.
  • the controller 350 registers the first characteristic information among the candidates selected by reflecting the group-specific characteristic information of the second font, which is distinguished from the first font and whose characteristic information is registered before the first font. You may.
  • a second font named “Rix report” in which characteristic information (characteristic information registered in the first font) of “modern” and “report” is registered, and the control unit 350 provides the second font. If "company/public office” is registered as the image/object characteristic information, the controller 350 may additionally register "company/public office” in the characteristic information of the first font.
  • control unit 350 reflects the group-specific characteristic information of the second font, which is distinguished from the first font and whose characteristic information is registered before the first font, includes using the previously registered word of characteristic information as it is. .
  • the controller 350 controls the characteristic information For the unification of , "report", which is characteristic information about the first font, can be modified and registered as "report”.
  • 4 is an example of a relationship diagram generated by a font list collection and a characteristic register according to an embodiment of the present invention. It shows that specific characteristic information of 6 groups is registered in 4 fonts (Rix gothic, Rix squirrel, Rix coffee flavor, Rix language).
  • the control unit 350 connects each characteristic information and fonts with a link, so that one or more fonts corresponding to one characteristic information can be easily identified.
  • the control unit 350 connects the first characteristic information and the first font with a link.
  • a link indicating the first font is included in the data structure of the first characteristic information, or a link indicating the first characteristic information is included in the data structure of the characteristic information of the first font.
  • the controller 350 may search for a third font in which the first characteristic information is registered and connect the first characteristic information and the third font with a link. In this case, since the first characteristic information is connected to the first font and the third font, the controller 350 may include the first font and the third font in the recommended font list in response to the first characteristic information.
  • the font characteristic intelligent analyzer 353 transmits the characteristic information transmitted by the client 100 or an area such as a document/text/website to which the client 100 intends to apply the font. Font recommendation information is generated using the information extracted from .
  • FIG. 5 is a diagram illustrating a process of recommending a font by an intelligent font characteristic analyzer according to an embodiment of the present invention.
  • the font characteristic intelligent analyzer 353 generates a similarity group by measuring the similarity of the font based on the multidimensional characteristic of the font.
  • a similarity group can be created by tying fonts with close integrated distances for each characteristic of the font.
  • the font characteristic intelligent analyzer measures the similarity between fonts and creates a group according to the similarity.
  • Characteristics of fonts have “Typefaces” group, “Style” group, “Emotional” group, “Use” group, “Image/Things” group, and “Custom” group, each group includes various characteristics.
  • the characteristic intelligent analyzer 353 selects a group to include the characteristic and adds it as a characteristic within the selected group.
  • the font characteristic intelligent analyzer 353 may assign a weight according to a group to which the font characteristic belongs. Give the highest weight to the 1st group, "Great Font Classification", the 2nd group, “Style”, to the 2nd highest weight, the 3rd group to give the 3rd highest weight to the "Emotional” group, and the 4th group to "Use” Each weight can be assigned to the group, the 5th group, the “image/object” group, and the 6th group, the “user-defined” group.
  • the font characteristic intelligent analyzer 353 can strengthen the characteristics of the font by additionally giving a weight of the characteristic corresponding to the search word to the fonts added to the user's font list among the fonts searched by the user with a specific word. have.
  • similarities between fonts are classified and grouped according to whether each characteristic is included and the strength of the characteristic. For similarity classification, it can be classified using unsupervised learning of machine learning.
  • the server 300 may receive characteristic information of a font desired to be used from the client 100 and provide it to the intelligent font characteristic analyzer 353 .
  • the server 300 receives a document file, text, or website address, image file, video file, etc. to which the font is to be applied from the client 100, and extracts context characteristic information from the received information.
  • the control unit 350 of the server 300 collects the name of the document file, the word appearing in the document or text, or the characteristic of the website, the text explanatory data for the image file or the video file, and the like to collect context characteristic information. Extraction is an embodiment.
  • the font characteristic intelligent analyzer 353 retrieves the characteristic information of the font.
  • the characteristic information of the font means that the font name, style, emotion, use, user, or image/thing characteristic information is assigned to the font as described in FIGS. 3 and 4 above.
  • the font characteristic intelligent analyzer 353 compares the font characteristic information with the context characteristic information of a document or web page to which the font is to be applied, selects the font characteristic information with high similarity or the same, and selects one or more fonts having such font characteristic information. It can be presented as a list or as a list.
  • the font characteristic information may also have a weight
  • the font characteristic intelligent analyzer 353 performs characteristic-based font intelligent curation to generate an intelligent characteristic list, and accordingly, the font characteristic intelligent analyzer 353 generates a font You can print a list.
  • FIG. 6 is a diagram illustrating a process of extracting a font list in response to context characteristic information according to an embodiment of the present invention. A look at the relationship diagram between the font characteristic information and the font in FIG. 4 is based on the presented example.
  • the font characteristic intelligent analyzer 353 receives context characteristic information from the client 100 .
  • the client 100 may select the context characteristic information accurately and transmit it to the server 300, or the client 100 transmits a file, text, image, video, etc. related to the context to the server 300, and the server This can be analyzed.
  • context characteristic information called "#diary" is extracted.
  • characteristic information of a diary is indicated by a circle.
  • What the server 300 secures or calculates as the context characteristic information is a state in which there is no characteristic information other than the purpose characteristic information.
  • the font characteristic intelligent analyzer 353 searches for characteristic information of “#diary” corresponding to “use characteristic information” of the font in the relation diagram. As a result, two fonts were found as fonts with characteristic information of "#diary”: “Rix Heo” and “Rix Coffee Flavor”.
  • the font characteristic intelligent analyzer 353 compares the correlation with the characteristic information of “#diary” among them, and selects “Rix Heo” and “Rix Coffee Flavor” as the first priority font, “Rix Squirrel” and “Rix Gothic” can be presented as a secondary font.
  • the font characteristic intelligent analyzer 353 may generate a similarity group according to the similarity of the font in order to recommend the font by reflecting the context characteristic information and the multidimensional characteristic information of the font. For example, based on the font list collection and characteristic register 351 of FIG. 3 or the result selected by the client 100 in the recommendation process, the font characteristic intelligent analyzer 353 performs the font characteristics based on the newly assigned font characteristics. You can measure the similarity and create similarity groups according to the similarity of fonts. The font characteristic analyzer 353 recommends similar fonts to the font selected by the client 100 by inputting a specific word in the search or by the client 100 .
  • the font characteristic intelligent analyzer 353 uses the characteristic information input by the client 100 or the context characteristic information extracted by analysis by the server 300 i) A font having the corresponding characteristic information as the name or meta information of the font A list of fonts, ii) a list of fonts having the corresponding characteristic information as the characteristic information of the font, and iii) a list of fonts having a high similarity to the font of i) or ii) above can be generated.
  • the control unit 350 compares the group-specific characteristic information of the fonts with the context or context characteristic information, and a plurality of previously registered characteristic information It is possible to create a list of recommended fonts composed of any one or more of the fonts.
  • the controller 350 may select a font corresponding to the context or context characteristic information.
  • the control unit 350 may select the first characteristic information Fonts with the same are also included in the recommended font list.
  • FIG. 7 is a view showing a similarity measurement process of fonts according to an embodiment of the present invention.
  • FIG. 7 shows a process of generating a similarity group based on a weight and a pattern of specific information.
  • the intelligent font characteristic analyzer 353 may be integrally integrated with the control unit 350 , and in this case, the control unit 350 provides all functions provided by the intelligent font characteristic analyzer 353 .
  • the font characteristic intelligent analyzer 353 may measure the similarity of the font after strengthening the characteristics of the font by giving weight to each characteristic information. First, the font characteristic intelligent analyzer 353 may give weight to the characteristic information of the font according to design characteristics and tendencies and the strength of the corresponding characteristics (S11). For the "Rix Love Diary" font, a weight of 100 can be assigned to the "#Trendy” feature, a weight of 10 to the "# Very” feature, and a weight of 50 to the "#Love” feature. Depending on the weight, the characteristics of the font will have more diverse patterns and at the same time, fonts with similar patterns will be more clearly revealed.
  • the font characteristic intelligent analyzer 353 creates a similarity group using the weighted pattern (S12).
  • a similarity group can be created by tying fonts with close integrated distances for each characteristic of the font.
  • fonts having similar characteristic information can be grouped using a K-means clustering method among unsupervised learning clustering models of machine learning. Group numbers can be assigned to the grouped fonts in this way.
  • the font characteristic intelligent analyzer 353 outputs a group of fonts grouped by similarity (S13).
  • the weighting method and the K-means clustering method are only examples, and similarity of characteristics can be measured in various ways.
  • the font characteristic intelligent analyzer 353 may use a clustering method to determine similarity between font characteristics.
  • the clustering method is one of the machine learning techniques that group similar data together.
  • K-means clustering K-means clustering, DBSCAN algorithm, or the like may be used.
  • K-means clustering is a center-based clustering algorithm, and it is a method of grouping fonts that are close in distance based on the center of a certain group into the same group. You can specify the number of groups (clusters) and group the fonts that are clustered around the center of each group into the same group. Being able to arbitrarily adjust the number of groups can be an advantage.
  • DBSCAN is a density-based clustering algorithm that groups neighboring fonts into the same group based on characteristics. Creates clusters of unspecified shapes by calculating the density between font data. Since the group is automatically determined compared to the K-means clustering algorithm, the number of groups (clusters) cannot be specified.
  • grouping methods are various such as Mean-Shift Clustering, Gaussian Mixture Model (GMM), EM Clustering (Expectation-Maximization Clustering), and Agglomerative Hierarchical Clustering.
  • the font characteristic intelligent analyzer 353 may use various clustering methods to measure the similarity between font characteristics, and the use of K-means clustering in the description is only one example.
  • the font characteristic intelligent analyzer 353 may measure the similarity by using a method such as word2vec or LSA to measure the similarity between font characteristics.
  • the controller 350 compares the pattern of characteristic information of the first font with the pattern of characteristic information of the third font. In addition, when the distance between the characteristic information as a result of the comparison is less than or equal to a predetermined standard, the controller 350 may group the first font and the third font into similar groups.
  • FIG. 8 is a diagram showing the operation process of the font use list intelligent analyzer according to an embodiment of the present invention.
  • the control unit 350 uses the received identification information A list of recommended fonts reflecting the user's characteristics can be created.
  • the controller 350 generates a list of preferred fonts by using the identification information of the first user. Also, the control unit 350 generates a list of preferred fonts of the second user having a similarity to the list of preferred fonts of the first user. Then, the controller 350 selects a similar user group (general/design/company, etc.) using the user's identification information to generate a font list of the selected user group. In addition, a recommended font list may be generated using the generated font lists. Let's take a closer look.
  • the font usage list intelligent analyzer 354 may recommend a font based on the list of fonts being used by the client 100 .
  • the font use list intelligent analyzer 354 determines the similarity of the font lists being used by the users who log in to the client 100, and configures a list of fonts used together (preferred font list) when using a specific font. have.
  • the whole process is that when the font use list intelligent analyzer 354 receives the user's font list, it analyzes the general user font list, analyzes the designer font list, and also analyzes the font list for each company/organization, and then integrates the user font list and Automatically generate characteristic information.
  • the font use list intelligent analyzer 354 can automatically generate and output the characteristics of the user's font list and the user's font list, and additionally use them to input the font list intelligent relationship analyzer to the relationship diagram of the font lists. can create
  • the font use list intelligent analyzer 354 in response to the user's font list provided by the client, the font use list intelligent analyzer 354 combines the user's identification information with the font list identification information as a list name when registering characteristic information in the My Font list. to create the name of the font list. For example, it is possible to create something like “User123 font list 2", and input "#report” and "#latest", which are characteristic information of the user, as characteristics of the user.
  • the font use list intelligent analyzer 354 may generate intelligent characteristic information in the My Font list. Characteristic information may be generated for each group in response to the previously created name "#User123FontList2". In an embodiment, the font use list intelligent analyzer 354 may generate "#Gothic” and “#Basic” as style characteristic information. The font usage list intelligent analyzer 354 may generate "#modern” as emotional characteristic information.
  • the font usage list intelligent analyzer 354 may generate "#report", "#text", and "#business” as usage characteristic information.
  • the font use list intelligent analyzer 354 may generate "#report” and “#latest” as user characteristic information, and create "#school” as image/object characteristic information.
  • the font use list intelligent analyzer 354 may use the generated characteristic information to generate a relationship diagram, which is a result of the relationship diagram analysis as described above with reference to FIG. 4 .
  • the font list integration of the user of FIG. 8 and the generation of characteristic information may be performed at regular time intervals. Alternatively, this can be done when the user adds or deletes a specific font from the list.
  • FIG. 9 is a diagram illustrating a process of recommending a font based on a font use list according to an embodiment of the present invention.
  • the client 100 may provide characteristic information of a font to be used to the server 300 , or may provide information on selecting a specific font to the server 300 .
  • the font usage list intelligent analyzer 354 may search for preference similarity of fonts using the provided font information.
  • the font use list intelligent analyzer 354 searches for similarity between users using the information generated in the process of FIG. 8 and the user identification information provided by the client 100, or general user/designer/company-group-specific fonts Retrieve list properties.
  • a list of preferred fonts of the second user similar to the first user is generated. Also, as a result of searching the font list characteristics for each general user/designer/company-organization, the font list of the user group is created.
  • a list of fonts suitable for the user's preference that is, a list of user-based fonts is provided.
  • the font use list intelligent analyzer 354 may provide a popular font Top 20/recommended font Top 20/recommended font list 20, etc. by using the curation result.
  • the font use list intelligent analyzer 354 receives characteristic information called “report”. Then, the font use list intelligent analyzer 354 may present "#User123FontList2", which was the previously created font list.
  • the font use list intelligent analyzer 354 additionally uses the characteristic information of "report” and the characteristic information such as "Gothic/Basic/Modern/Text/Business/Report/Latest/School/Company” calculated by it. A list of fonts can be calculated. As a result, the font use list intelligent analyzer 354 also includes "#KimWebD's report font list” corresponding to the designer font list characteristics, and "#Web designer group's suggested font list” corresponding to the font list characteristics for each company/organization. can be printed out.
  • the font usage list intelligent analyzer 354 provides a "Rix acacia” to users who search for or use the “Rix love diary” font if there are many cases of using the "Rix acacia” font among users who use the "Rix love diary” font. You can recommend a font.
  • a list-based recommended font list may be added.
  • the user's font list can be divided into a basic font list, a favorite font list, a font list by use, and a list of all fonts that are integrated. And, in the font list set for each user, when the user logs in to the client 100 , the server 300 can check the stored list using the login information of the user. Alternatively, the client 100 may transmit information on the basic font list/favorite font list/use-specific font list set by the user to the server 300 .
  • the default font list refers to a font list that is not assigned a separate name.
  • the favorite font list refers to a font list that is managed by grouping only frequently used or favorite fonts.
  • the font list by use is a list of fonts that the user organizes and manages for a specific purpose, and various names such as "Cyan font list”, “Report font list”, and "Web design font list” can be given.
  • the integrated full font list means the entire set of fonts included in any font list.
  • the font use list intelligent analyzer 354 can make a recommended list of fonts by determining the similarity of each font by using the word-to-vector (Word2Vec) algorithm learning method among the machine learning methods for the entire font list.
  • the word-to-vector algorithm learning method can measure the similarity of fonts in the font list as words.
  • similarity of words constituting characteristic information of fonts may be measured.
  • the font use list intelligent analyzer 354 can classify the similarity of the fonts based on the user list by learning the word-to-vector algorithm after making an integrated font list for each user. Since the similarity of the classified font is based on the user's usage pattern, it has a tendency different from the similarity based on the characteristic information of the font, thereby indicating the similarity according to the user's preference.
  • the similarity classification can be performed after making it closer to the user's actual usage pattern by giving weight to the duplicate inclusion of the same font in each font list.
  • the font usage list intelligent analyzer 354 may measure the similarity between fonts using machine learning.
  • the font usage list intelligent analyzer 354 may use the word2vec algorithm for determining the similarity between words in order to measure the similarity of the font usage list.
  • the Word2vec algorithm is one of the embedding models, which is a natural language processing (NLP) technique of machine learning. You can find similarities between words by learning word embeddings.
  • the user's font list is a list of fonts added according to the user's tendency and purpose of use. Fonts included in each list can be seen as being in a context with a certain purpose, and fonts can be seen as having meaning within the context. If the user's font list is viewed as a sentence with a single meaning, the fonts can be viewed as words within the sentence.
  • the font usage list intelligent analyzer 354 may find similarities between fonts by using a word embedding algorithm using this feature.
  • LSA latent semantic analysis
  • Globe Globe
  • FText FastText
  • LSA Latent Semantic Analysis, LSA uses DTM (Document Term Matrix) or TF-IDF (Term Frequency - Inverse Document Frequency) truncated SVD (Singular Value Decomposition) to reduce dimensions, and the potential meaning of words
  • DTM Document Term Matrix
  • TF-IDF Term Frequency - Inverse Document Frequency
  • SVD Single Value Decomposition
  • Global Vectors for Word Representation is a word embedding methodology that uses count-based and prediction-based. It is an algorithm that supplements the shortcomings of count-based LSA (Latent Semantic Analysis) and prediction-based Word2Vec.
  • FastText is an algorithm that extends Word2Vec, and learns by considering that multiple subwords may exist within one word.
  • Word2Vec algorithm of machine learning to analyze the similarity between fonts using the user's font list is just one example, and various algorithms can be used.
  • the font use list intelligent analyzer 354 may measure the preference similarity of the font based on the user's font use tendency using a word-to-vector learning method or other machine learning and construct a recommendation list.
  • the font use list intelligent analyzer 354 may configure the user list for each font by transforming the user's font list. If a user list for each font is configured, users with a similar tendency can be found through the font usage pattern, and the user's font list can be recommended. For example, if user user-0001 likes to use the "Rix Love Diary" font, "Rix Toy Story", and “Rix Gwangalli” fonts, and there is user user-0002 who likes fonts similar to these fonts, user user- We can recommend the font list of user user-0002 to 0001.
  • the above-described method for recommending fonts based on a user font list reflects each user's font preference and usage characteristics.
  • the font use list intelligent analyzer 354 updates the similarity group to which the user belongs according to the method by which a user adds a font to his/her font list, the method of liking or designating a favorite font, and the font list created for each purpose can do.
  • the font use list intelligent analyzer 354 may provide fonts suitable for the updated group as recommended fonts to the client logged in by the corresponding user.
  • the font usage list intelligent analyzer 354 may recommend popular fonts by integrating the font usage information on the user list.
  • the font usage list intelligent analyzer 354 may list the fonts most frequently used by creating aggregate information on the fonts used by all users to calculate the order of popularity of the fonts.
  • the font use list intelligent analyzer 354 can recommend fonts by recording and managing aggregate information by period, reflecting changes in popularity by period.
  • the user's font list can be managed by dividing it into a general user group, a designer group, and a group by company/organization.
  • the general user group is a general type used by users who do not select a user type by making a font list.
  • the designer group is a user group in which the user type is designated as designer, and a designer group for each field can be created.
  • a designer group can be viewed as a concept corresponding to an artist group in a music service.
  • the company/organizational group is a user group with a user type designated as a company/organizational type, and a font list used by companies and organizations is created and used. In this way, if the font list is managed separately for each user group, it becomes easier to recommend a font suitable for the user's purpose.
  • the font use list intelligent analyzer 354 analyzes the font list created by the user to measure the similarity between the user-based font preference and the user. And it creates a list of popular fonts for all users.
  • the font list can be divided into a general user group, a designer group, and a company/organizational group by user type.
  • the user's font list includes a basic font list, a favorite font list, a font list by use, and an integrated font list.
  • the font usage list intelligent analyzer 354 analyzes the similarity for the entire user font list that integrates the entire user's font list.
  • the entire integrated user font list also has a basic font list, a favorite font list, a font list by use, and an integrated font list.
  • the font usage list intelligent analyzer 354 analyzes the similarity of the font list incorporating the user font list in the usage type group.
  • the integrated user font list in the type group also includes a basic font list, a favorite font list, a font list by use, and an integrated font list.
  • the font usage list intelligent analyzer 354 analyzes the similarity of the user's preferred fonts with respect to the user-specific font list in the usage type group.
  • the font use list intelligent analyzer 354 recommends a font having a high preference similarity with respect to a font searched or selected by the user using the measured user preference font similarity information.
  • the font use list intelligent analyzer 354 may apply the same font as a weight to the integrated font list among the user-specific font lists. If a font included in the basic font list also exists in the favorite font list, the font can be included in the integrated font list as duplicates.
  • the font use list intelligent analyzer 354 may measure the similarity of the user font list using a machine learning-based similarity analysis method.
  • the font usage list intelligent analyzer 354 generates a user list for each font by transforming the user font list.
  • the font use list intelligent analyzer 354 configures a user list for each font by adding a user who uses each font to the user list for the font.
  • the font use list intelligent analyzer 354 measures the similarity between users by analyzing the similarity with respect to the user list for each font. And the font use list intelligent analyzer 354 recommends a font list of other users with similar tendencies to the user by using the measured similarity information between users.
  • the font use list intelligent analyzer 354 analyzes the fonts included in the user font list, extracts characteristics common to the fonts, and assigns them to the corresponding font list as characteristics. Characteristics that include all of them in common and those that contain more than half of the font list or a specific ratio are given as characteristics of the font list.
  • the font use list intelligent analyzer 354 may give weights to characteristics according to the number of fonts including the corresponding characteristics. When a characteristic is assigned to the font list, the similarity between the font lists is classified and grouped according to whether or not the characteristic is included and the strength of the characteristic. For similarity classification, it can be classified using the unsupervised learning method of machine learning.
  • the font use list intelligent analyzer 354 adds the classified group information to the font list information and uses it when recommending a font list suitable for the searched font characteristics and fonts.
  • the font use list intelligent analyzer 354 can know the number of users for each font by using the user list for each font. Using the number of users per font, you can create a list of popular fonts for all users.
  • the font usage list intelligent analyzer 354 may make a list of popular fonts for each type by creating a user list for each font for each usage type and for each type of list.
  • the aforementioned font use list intelligent analyzer 354 may be integrally included in the control unit 350 . Accordingly, the controller 350 uses any one or more of a word embedding similarity determination algorithm including a word-to-vector (Word2Vec) method, a latent semantic analysis method, or a globe or fast text method, and a font belonging to the preferred font list of the first user.
  • the second user's preferred font list may be generated by measuring the similarity between the characteristic information of the fonts and the characteristic information of the font or fonts belonging to the second user's preferred font list.
  • the font trend intelligent analyzer 355 recommends fonts based on big data, and generates font trend information by analyzing the trends of the portal site and information collected from SNS such as Instagram, and font cloud services in an embodiment.
  • the font trend intelligent analyzer 355 may perform trend collection using the trend API of the portal site.
  • the font trend intelligent analyzer 355 may collect tag information used in a hashtag-based SNS site such as Instagram.
  • the font trend intelligent analyzer 355 recommends a trend font by collecting a list of popular fonts of the font cloud service.
  • the font trend intelligent analyzer 355 may collect characteristic information or font information used or searched in the font cloud.
  • the font trend intelligent analyzer 355 may collect a search trend (portal search word trend) for each font list for a portal with a high usage rate by using the search word trend API.
  • Instagram hashtags can also collect information on how many times each font name has been tagged during a specified period.
  • the font trend intelligent analyzer 355 may collect tagging information of hashtags from multiple SNS sites. For example, the font trend intelligent analyzer 355 may collect the cumulative number of tagged font names and the number of popular articles by period, and check the change in popularity through the amount of change in the cumulative number of times.
  • the list of popular fonts of Font Cloud Service can be collected through each font site.
  • Popular fonts of the Font Cloud service are determined based on the number of downloads, usage, and popularity rankings of users.
  • the font trend intelligent analyzer 355 configures a list of recommended trend fonts based on big data by adding up the trend of the portal site, the popularity on SNS such as Instagram, and the information of the font cloud service.
  • the font trend intelligent analyzer 355 may configure the final recommended trend font list by assigning weights to each source of the collected trend information or according to the importance or priority of the information. For example, a weight of 3 can be given to the trend data of a portal site, a weight of 2 can be given to the popularity of SNS, and a weight of 1 can be given to the font cloud service data.
  • the font trend intelligent analyzer 355 can provide intelligent font trend curation, and it creates a font list reflecting the font trend information by integrating the collected information such as the font trend Top 100 or the font trend-based recommended font Top 20 can do.
  • the communication unit 310 receives portal trend collection information, SNS hashtag trend collection information, font use, or search trend collection information.
  • the font trend intelligent analyzer 355 or the control unit 350 including the font trend intelligent analyzer 355 integrally may generate a font list by using the received collection information.
  • the font trend intelligent analyzer 355 may use a search index, number of searches, etc. provided by the portal search trend API. In addition, the font trend intelligent analyzer 355 may collect the number of posts, the number of popular posts, etc. as a result of the Instagram hash characteristic trend. In addition, the font trend intelligent analyzer 355 may calculate the number of activations, the number of font lists included, the number of searches, etc. as a result of the font cloud trend.
  • the font trend intelligent analyzer 355 creates a list of font trends or font trend-based recommended fonts by collecting the collected and calculated results.
  • the font big data trend intelligent analyzer 355 generates font trend information by analyzing the trends of the portal site and information collected from SNS such as Instagram, and font cloud services.
  • the font big data trend intelligent analyzer 355 may collect search word trends of the portal site for fonts included in the entire font list, and the collected trend information is provided as a search index or number of searches.
  • the font big data trend intelligent analyzer 355 may record the collected information for each collection period and accumulate and store changes in the popularity of the font.
  • the font characteristic intelligent analyzer 353, the font use list intelligent analyzer 354, and the font trend intelligent analyzer 355 were examined as a method of recommending fonts.
  • Each font recommendation method has a different method of classifying fonts and determining the similarity and popularity order. Accordingly, the font intelligent curation service provider 358 may present all the recommended font lists generated by each analyzer 353 , 354 , 355 to the user, and may present only one recommended font list by integrating them. Or, you can create and provide a list of some recommended fonts.
  • the font intelligent curation service provider 358 divides the recommended font list, popular font list, recommended user's font list, and font trend list into a list of font trends to the client 100. provided, these lists may be displayed by the client 100 or on a web page of the server 300 .
  • the server 300 or the client 100 displays a font list matching the font name or search word at the top, and displays a user list-based recommendation list below it, and displays a recommendation list according to the font similarity below it.
  • a "recommended font list” can be displayed.
  • the server 300 or the client 100 may display a list of popular fonts of all users based on the user font list as a "popular font list”.
  • the server 300 or the client 100 may display the user's font list as a "recommended user font list” and recommend the user font list itself.
  • the server 300 or the client 100 may display a separate "font trend list" according to the order of popularity based on big data.
  • FIG. 11 is a diagram illustrating an operation process of a font intelligent curation service provider according to an embodiment of the present invention.
  • the font intelligent curation service provider 358 is a font characteristic-based font similarity and user use generated by the font characteristic intelligent analyzer 353, the font use list intelligent analyzer 354, and the font big data trend intelligent analyzer 355.
  • One or more fonts or font lists are recommended to users by using pattern-based font preference similarity, similarity between users, popular font list, and font trend information.
  • the first font (list), the second font (list), ..., the n-th font list) correspond to a font or a font list.
  • the font intelligent curation service provider 358 creates a recommended font list using these fonts or font list.
  • the server 300 When the client 100 transmits a specific word to the server 300 to search for a word including the name of the font, the name of an object or image, the type of the font, the characteristics of the font, the object of interest, and the like, the server 300 is Creates a name search list by searching for font names that contain the word.
  • the font characteristic intelligent analyzer 353 searches for the characteristics of the corresponding word in the large font classification group, style group, emotion group, use group, image/object group, and user-specified group on the new classification system to generate a characteristic inclusion list. .
  • the font characteristic intelligent analyzer 353 generates a primary font list by removing duplicate fonts from the name search list and the characteristic inclusion list.
  • the primary font list includes one or two or more of a first font (list) to an n-th font (list).
  • the font intelligent curation service provider 358 creates a group recommended font list composed of fonts belonging to the similarity group based on the same font characteristics as the fonts in the primary font list.
  • the font intelligent curation service provider 358 selects only fonts whose characteristic information of fonts included in the group recommendation list includes all common characteristics of the fonts in the primary font list or has an inclusion relationship greater than or equal to the characteristic ratio, and selects the final group recommended font create a list
  • the font intelligent curation service provider 358 creates a font list according to the user pattern-based font preference similarity including fonts included in the primary font list.
  • the font intelligent curation service provider 358 generates a font list with high similarity for a font list reconstructed only with fonts having a high weight for a common characteristic among the characteristic inclusion list and fonts included in the name search list in order to increase the similarity accuracy. can do.
  • the font intelligent curation service provider 358 creates a list of user list-based recommended fonts by listing them in the order of the highest similarity values as a user pattern-based font preference similarity recommendation list.
  • the font intelligent curation service provider 358 may generate a final recommended font list by integrating the group recommended font list generated based on the primary font list and the user list based recommended font list.
  • the intelligent font curation service provider 358 creates a list of users with similar tendencies based on the similarity between users for other users with similar tendencies to the user.
  • the user list with similar propensity is listed in the order of the highest similarity value between users.
  • the font list of users with the highest similarity in the list of similar users is composed of the recommended user font list.
  • the font intelligent curation service provider 358 configures a virtual user list including a primary font list for the currently searched font in order to increase the similarity accuracy for the currently searched font, and holds the virtual user list configured in this way.
  • a user's font list having a high degree of similarity between users may be configured as a recommended user font list.
  • the font intelligent curation service provider 358 uses the font usage aggregate information for all users generated by the font usage list intelligent analyzer 354, the font intelligent curation service provider 358 creates a list of popular fonts.
  • the font intelligent curation service provider 358 creates a font trend list.
  • the font intelligent curation service provider 358 provides the user with a primary font list, a font recommendation list, a recommended user's font list, a popular font list, and a font trend list generated through each recommendation method.
  • the font intelligent curation service provider 358 uses the information calculated in the process of generating a recommended font list using the font or font list generated by each of the analyzers 353, 354, 355 to view previous results can be updated. For example, the font intelligent curation service provider 358 updates any one or more of the previous first font (list) to n-th font (list) by performing feedback (S15) in the process of generating the recommended font list. can do.
  • control unit 350 including the intelligent font curation service provider 358 or the intelligent font curation service provider 358 integrally generates one recommended font list and then generates a second recommended font list. Also, after generating the second recommended font list, the first recommended font list may be updated using the second recommended font list.
  • the control unit 350 of the server 300 may set and store all fonts selected and used by each user as a user-specific font list.
  • the control unit 350 may configure one search list by integrating the search history.
  • the control unit 350 may configure a separate list of favorite fonts for fonts that the user likes or registered in favorites.
  • the control unit 350 or the font use list intelligent analyzer 354 that is a sub-component of the control unit 350 may perform the above-described operation.
  • the font intelligent curation service provider 358 configures the user font list by listing the fonts selected and used by each user.
  • the list of user fonts can change whenever the user adds or removes fonts.
  • the font use list intelligent analyzer 354 performs re-learning on the changed user list using a machine learning technique, and recalculates the similarity between the font and the user. As a result, the font intelligent curation service provider 358 may recommend a font reflecting user preference.
  • the client 100 may transmit a search word to the server 300 to search for a specific font.
  • the name of the font, the keyword of interest, etc. are input as a search word as an embodiment.
  • the keyword input by the user into the client 100 is not registered as font characteristic information, the name of the font is entered incorrectly, or the keyword is misspelled, the desired font may not be searched.
  • the controller 350 of the server 300 registers synonyms for the name of the font and the characteristics of the font, and may suggest correct search results and recommended fonts even for the user's erroneous input.
  • the controller 350 may register “love” as a synonym for "love”, and “trend” ("Trand"), “trend” ("Trendy”), " trend” and “trendy” can be registered as synonyms.
  • the controller 350 may register "sensory”, “sensory”, “sense”, “sense”, etc. as synonyms for characteristic information of "sensory”, which is an adjective type.
  • the controller 350 may register a keyword having a high similarity between a currently popular buzzword and a characteristic of a font as a synonym. For example, when there is no font characteristic information for the keyword "gag", the control unit 350 may register as new characteristic information of the font. It can be registered as a synonym for characteristic information.
  • the control unit 350 may also register seasonal keywords such as “cherry blossom festival”, “flower viewing”, and “spring breeze” as user-defined font characteristic information, but may also be registered as a synonym for the characteristic “spring”, which is the existing font characteristic information. have. In this way, registration of synonyms is a way to more flexibly utilize the characteristics of fonts.
  • control unit 350 adds or changes font characteristics, the similarity between fonts may be changed due to a change in font characteristic information.
  • the controller 350 registers a synonym, it does not affect the similarity between fonts, so that it can be used more flexibly.
  • the controller 350 may register synonyms for each characteristic information in the step of inputting the characteristic information of the font. Even after the characteristic information is registered, the controller 350 can freely add and delete synonyms to the characteristic information.
  • the control unit 350 stores the synonym candidate separately, and the control unit 350 automatically or manually by a separate administrator later stores the meaning of the synonym candidate word Based on this, it can be registered as a synonym for the existing font name and characteristic information.
  • the registered thesaurus can be used as a thesaurus for each font name and characteristic information.
  • the AI recommended font service provided can help users select and distinguish fonts into various groups in order to actively utilize machine learning technology. This goes beyond the classification system based on the design style of the existing font text, and the server 300 applies a new classification system that considers various characteristics such as the use, function, and design of the font to the font classification system to have various characteristic information. Classify or group fonts using a classification system.
  • a rule that can be easily assigned like a tag is applied rather than a strict naming rule (naming rule) as a way to increase the convenience of data processing for new characteristic information of a font.
  • naming rule a strict naming rule
  • it can be made compatible with the tag naming method of various SNS/web pages.
  • various characteristic information may be designated for each font.
  • the font "Rix neo-gothic" applies a new classification system with various characteristic information, so #text, #gothic, #readability, #serif, #concise, #business, # It can be classified as a font having characteristic information such as documents and #proposals, and such characteristic information can be expanded and changed according to the user's usage trend.
  • information on fonts applied to the contents of a specific medium also uses input characteristic information such as tags, or through the intelligent font trend analyzer 355 . Since they can be collected, users can easily identify a preferred font among various fonts.
  • the server graphs the degree of association of characteristic information for each font.
  • the characteristic value of the first font is displayed on the vertical axis in response to the characteristic information arranged on the horizontal axis.
  • the characteristic value of the second font is displayed on the vertical axis corresponding to the characteristic information arranged on the horizontal axis.
  • the control unit 350 may recommend the first font in the context characteristic information of “text”.
  • FIG. 13 is a diagram in which a server arranges fonts in a two-dimensional space using characteristic values of two pieces of characteristic information for each font according to an embodiment of the present invention.
  • the server can arrange the fonts in a two-dimensional space using two axes (X-first characteristic information characteristic value, Y-second characteristic information characteristic value).
  • Each font has a characteristic value of the first characteristic information and a characteristic value of the second characteristic information. This characteristic value may be a weighted value.
  • the server may generate the first font list/second font list/third font list according to the location where these fonts are arranged and the distance between them.
  • each font may be distributed according to the characteristic value of the characteristic information in the N-dimensional space, and the server may generate a font list according to the density of these distributions. And fonts included in the same font list can be presented together when the server recommends a font.
  • FIG. 14 is a diagram in which the server according to an embodiment of the present invention arranges users in a two-dimensional space by using the preference of two font lists for each user.
  • the server can place users in a two-dimensional space using two axes (X-Preference per user for the first font list, Y-Preference per user for the second font list). have.
  • the server may create the first user group/second user group/third user group according to the location where these users are arranged and the distance between them.
  • each user may be distributed according to their preferences in the M-dimensional space, and the server may create a user group according to the density of these distributions.
  • the server may recommend font lists of other users in the same group to users included in the same user group.
  • the server 300 may recommend a font list preferred by users user2/user3/user4 to a user who is user1 of the first user group.
  • AI recommendation font technology to which an embodiment of the present invention is applied provides a method of recommending a font that best corresponds to the information input by the user by adding various meta information (tags) to the font to classify and integrate the font in various ways.
  • Meta information about fonts is provided in the form of tags so that users can easily add them.
  • the AI object recognition function it is possible to recommend a "strawberry” image or a font that goes well with an object. It can be used as a method of converting the information recognized by AI object recognition into a string called “strawberry” and recommending the most suitable font for “strawberry”.
  • the meaning of the tag is not simply the meaning of a one-dimensional classification method between words and fonts, but since it has a relational network characteristic for the font and each meta information (tag) group, the tag is When it is set as the characteristic information of the font, it constitutes a relationship diagram as shown in FIG. 4 or 6 , so that the recommendation accuracy of a similar font can be increased.
  • the present invention is not necessarily limited to this embodiment, and all components are one or more within the scope of the present invention. They may be selectively combined to operate.
  • all of the components may be implemented as one independent hardware, some or all of the components are selectively combined to perform some or all of the functions of one or a plurality of hardware programs module
  • Such a computer program is stored in a computer-readable storage medium (Computer Readable Media), read and executed by the computer, thereby implementing the embodiment of the present invention.
  • the storage medium of the computer program includes a magnetic recording medium, an optical recording medium, and a storage medium including a semiconductor recording device.
  • the computer program implementing the embodiment of the present invention includes a program module that is transmitted in real time through an external device.

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Abstract

La présente invention porte sur un procédé de recommandation de police de caractères et sur un dispositif destiné à le mettre en œuvre. Le procédé de recommandation de police de caractères selon un mode de réalisation de la présente invention recommande une police de caractères qui reflète les informations caractéristiques de polices multidimensionnelles d'une police de caractères, la police de caractères préférée d'un utilisateur, et des tendances de polices de caractères.
PCT/KR2021/005071 2020-06-03 2021-04-22 Procédé de recommandation de police de caractères et dispositif destiné à le mettre en œuvre WO2021246642A1 (fr)

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KR1020200067011A KR102357939B1 (ko) 2020-06-03 2020-06-03 폰트를 추천하는 방법 및 이를 구현하는 장치
KR10-2020-0067011 2020-06-03

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KR102420159B1 (ko) * 2022-03-07 2022-07-13 주식회사 산돌 폰트 서비스 시스템의 웹 폰트 서비스 방법

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US11886793B2 (en) * 2021-09-03 2024-01-30 Adobe Inc. Textual design agent

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KR20210150638A (ko) 2021-12-13

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